Abstract
Automated legal reasoning and its application in smart contract is getting interest. In this context, ethical and legal concerns make it necessary for automated reasoners to justify in human-understandable terms the advice given. Logic Programming, specially Answer Set Programming, has a rich semantics and has been used to very concisely express complex knowledge. However, modelling vague concepts such as ambiguity and discretion cannot be expressed in top-down execution models based on Prolog, and in bottom-up execution models based on ASP the justifications are incomplete and/or not scalable. We propose to use s(CASP), a top-down execution model for predicate ASP, to model ambiguity and discretion following a set of patterns. We have implemented a framework, called s(LAW), to model, reason, and justify the applicable legislation and validate it by translating (and benchmarking) the criteria for the admission of students in public centers established by the “Comunidad de Madrid”.
This work has been partially supported by the Spanish Ministry of Science, Innovation and Universities, co-funded by EU FEDER Funds, through project grant InEDGEMobility RTI2018-095390-B-C33 (MCIU/AEI/FEDER, UE).
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Notes
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Organic Law 2/2006, May 3, last modified by Organic Law 3/2020, December 29.
- 2.
Decree 29/2013, of April 11, modified by Decree 11/2019, of March 5, of the Governing Council, on freedom of choice respecting school centers; Order 1240/2013, of April 17, of the Department of Education, Youth and Sports of Community of Madrid, modified by Order 1534/2019, of May 17, of the Department of Education and Research Community of Madrid; Resolution of July 31, 2013, of the General Directorate for the Improvement of the Quality of Education (regarding bilingual education); and Joint Resolution of the Deputy Department of Educational Policy and Educational Organization, of February 18, 2021 (https://bit.ly/3dAX22d).
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Arias, J., Moreno-Rebato, M., Rodriguez-García, J.A., Ossowski, S. (2021). Modeling Administrative Discretion Using Goal-Directed Answer Set Programming. In: Alba, E., et al. Advances in Artificial Intelligence. CAEPIA 2021. Lecture Notes in Computer Science(), vol 12882. Springer, Cham. https://doi.org/10.1007/978-3-030-85713-4_25
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